The Idea Behind Relational Management | Guidelines
Guidelines - Monika Karolina Kosiedowska

The Idea · Relational Management

Abstract relational structure in green light

Relational Management begins with a strategic observation: as AI makes some forms of analysis and knowledge work more accessible, lasting difference may depend increasingly on how organisations combine resources, learn across boundaries, coordinate action, and exercise judgment.

Begin with why Explore the premises

Technology changes what is possible. Relationships shape what becomes valuable.

This page presents the reasoning behind a developing management perspective. It distinguishes established knowledge from interpretation, working propositions, and questions that require further research.

01

Why Relational Management, why now

Access to capability is not the same as the ability to create value.

AI changes the speed and availability of some forms of knowledge work. It does not remove the organisational conditions needed to use them well.

Technology creates capacity. Relational and organisational conditions shape how that capacity is interpreted, coordinated, and used.

Organisations have long competed through resources, expertise, processes, technologies, and market position. These sources of advantage remain important. AI is changing the speed and scale at which some forms of analysis, content production, and problem solving can be performed.

This is not a claim that technology has stopped differentiating organisations. Advanced infrastructure, proprietary data, technical expertise, implementation quality, and access to complementary assets can still matter greatly. The more precise claim is that access to a tool does not determine the value created with it.

Outcomes also depend on whether people can question outputs, combine different forms of knowledge, surface disagreement, coordinate across boundaries, learn from feedback, and take responsibility for decisions. These processes are not purely technical. They have important relational and organisational dimensions.

The strategic question therefore changes. It is no longer only, "What technology do we possess?" It is also, "What can we learn, decide, and accomplish together that others will find difficult to reproduce?"

A group of experienced professionals engaged in a thoughtful working session
Learning, interpretation, and coordinated action retain important social and organisational dimensions, even when they are supported by AI systems. Editorial concept image created for Guidelines. It does not document a specific event.
02

The central proposition

Competitive advantage may become increasingly relational.

Comparable resources may produce different outcomes partly because organisations differ in how they combine knowledge, coordinate action, learn, and govern interdependence.

Relational Management seeks to explain why organisations with comparable resources and technologies may produce different outcomes by examining how relational conditions and processes shape access, interpretation, learning, coordination, and governance.

The perspective examines relationships within organisations and across organisational boundaries. It also examines interactions between people and AI systems, relationships among people mediated by AI, and the organisational arrangements through which the use of AI is governed.

Relational conditions include trust, interdependence, power, shared understanding, and expectations of responsibility. Governance arrangements define decision rights, accountability, monitoring, and the ability to challenge an action or decision. Together, these conditions influence processes such as knowledge exchange, interpretation, learning, coordination, and joint action.

The argument is conditional, not universal. Relationships are not automatically valuable, and they do not replace technology, strategy, markets, or operational excellence. Their strategic significance depends on what they enable, for whom, under what conditions, at what cost, and with what consequences.

Working proposition RM-P01: As AI-enabled and other technological capabilities become more widely accessible, the relational conditions and organisational capabilities through which they are used may become increasingly important sources of differentiation and competitive advantage.

Theoretical proposition in development. It requires conceptual refinement, clearly defined levels and boundary conditions, and empirical investigation.

03

Foundational premises

Three premises and their analytical implications.

The premises become useful when they change what we examine, compare, and seek to explain. They are starting points for inquiry, not conclusions that apply universally.

Premise A

Value is co-created.

Implication: The unit and level of analysis must be made explicit. Where value is co-created, the organisation cannot always be treated as a sealed and sufficient unit of analysis. Attention may need to extend to relationships among employees, leaders, customers, partners, institutions, and communities, including settings in which technologies support or mediate their interactions.

The analysis should identify the relevant actors, the type of relationship being examined, how contributions are combined, how decisions move across boundaries, and how value, risk, and responsibility are distributed.

Relational Management takes a multilevel perspective, but it does not assume that the same mechanisms operate identically at the individual, team, organisational, interorganisational, and ecosystem levels.

Analytical consequence: Depending on the research question, the relevant unit may be an individual, a dyadic relationship, a team, an organisation, an interorganisational relationship, a network, an ecosystem, or a human-AI work system.

Premise B

Relationships can be strategic resources.

Implication: Relational value must be demonstrated, not assumed. A relationship should not be classified as a strategic resource merely because it exists. Its strategic significance must be connected to an identifiable mechanism and outcome.

Such mechanisms may include access to complementary knowledge, credible cooperation, knowledge-sharing routines, faster coordination, joint problem solving, or learning that competitors may find difficult to reproduce.

The same relationship may support value creation in one context and create dependency, exclusion, rigidity, conflict, or risk in another. Relational conditions and relational outcomes therefore require separate assessment.

Analytical consequence: Diagnosis should examine both value-creating mechanisms and relational liabilities, including power asymmetry, exclusion, lock-in, coordination costs, and the unequal distribution of benefits and risks.

Premise C

Learning is relational and foundational.

Implication: Advantage may depend partly on how the system learns. When some forms of knowledge and analytical support become easier to access, an important difference may lie in how effectively people and organisational systems notice, interpret, question, retain, and apply knowledge.

AI can influence these processes by providing recommendations, generating content, detecting patterns, or supporting decisions. It can also reinforce error, bias, false confidence, or harmful routines when feedback, judgment, and accountability are weak.

This brings learning architecture into strategic analysis. Relevant elements include feedback channels, opportunities to question assumptions, psychologically safe conditions within teams, cross-boundary knowledge flows, experimentation, organisational memory, and the ability to challenge both human judgment and AI-generated output.

Analytical consequence: Research must distinguish productive learning from compliance, imitation, automation bias, and the reinforcement of existing errors or inequalities.

04

What this perspective proposes

A distinct lens, with explicit boundaries.

Credibility depends not only on what a perspective seeks to explain, but also on what it does not claim. The proposed contribution lies in connecting relational strategy, resource activation, knowledge integration, organisational learning, governance, human capital, and human-AI work systems in a shared explanatory perspective.

Relational Management proposes

Examine the conditions through which capability becomes value.

  • Study relationships as part of strategic and organisational analysis, not only as interpersonal context.
  • Examine how resources and existing capabilities are activated through knowledge exchange, interpretation, learning, coordination, and governance.
  • Distinguish interactions between people and AI systems, relationships among people mediated by AI, and organisational arrangements governing the use of AI.
  • Specify relevant actors, relationship type, level of analysis, mechanism, context, and outcome.
  • Ask how relational value is created, distributed, protected, constrained, and sometimes destroyed.
Relational Management does not claim

Replace existing theories or treat every relationship as beneficial.

  • It is not presented as an established scientific school.
  • It does not argue that relationships replace technology, strategy, markets, or operational excellence.
  • It does not assume that cooperation removes power, conflict, or competing interests.
  • It does not assume that AI systems are equivalent moral or relational agents.
  • It does not offer universal prescriptions before context and evidence are examined.
05

Principles of Relational Management

A disciplined way of seeing before acting.

These principles guide inquiry and practice. They are not substitutes for evidence, judgment, or context.

Evidence before assertion.

Separate established findings from interpretation, working propositions, hypotheses, and future research directions.

Mechanisms before labels.

Explain how relational conditions are expected to influence outcomes rather than treating relationship quality as a conclusion in itself.

Levels of analysis before generalization.

Specify whether a claim concerns individuals, teams, organisations, interorganisational relationships, networks, ecosystems, or human-AI work systems.

Power and distribution alongside value creation.

Examine who defines value, who contributes, who benefits, who bears risk, and who has the ability to challenge a decision.

Diagnosis before intervention.

Understand the system, its relationships, incentives, history, and constraints before recommending action.

Long-term value alongside short-term performance.

Consider whether immediate optimization strengthens or weakens the capacity to cooperate, learn, and create value over time.

06

Strategic tensions

Relational value must be examined through tensions, not simple prescriptions.

These tensions prevent the perspective from becoming a general call for more trust, more cooperation, or more relationships.

Trust and verification

Sufficient trust can enable action, knowledge sharing, and cooperation. Responsible management also requires evidence, monitoring, challenge, and the ability to question both people and AI-generated outputs.

Openness and protection

Knowledge often becomes more usable when it can move across relevant boundaries. Organisations must also protect confidentiality, legitimate interests, intellectual assets, and the people who may be exposed by greater transparency.

Cooperation and power

Shared goals do not remove differences in authority, dependence, bargaining position, or the ability to define whose contribution, interests, and outcomes matter.

Efficiency and resilience

Optimizing a process may improve immediate performance while weakening redundancy, judgment, learning, or the relationships needed to respond when conditions change.

Automation and human agency

AI can extend or automate organisational capabilities. Decisions about judgment, responsibility, explanation, contestability, and the right to challenge an outcome remain organisational and relational choices.

Continue exploring

From the idea to a researchable framework.

The Framework defines the analytical domains, key concepts, relational capabilities, levels of analysis, and boundaries of Relational Management. The Research page documents the intellectual foundations, working propositions, and questions that still require investigation.

Explore the Framework View the Research